WiG:基于wifi的手势识别系统

Wenfeng He, Kaishun Wu, Yongpan Zou, Zhong Ming
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引用次数: 138

摘要

最近,由于手势识别在家庭自动化、移动游戏等日常生活中的各种应用,越来越引起学术界和工业界的强烈兴趣。目前的手势识别方法主要包括基于视觉的、基于传感器的和基于射频的,但它们都有一定的局限性,阻碍了它们在某些场景中的实际应用。例如,基于视觉的方法在光线不足的情况下不能很好地工作,而基于传感器的方法需要用户佩戴设备。为了解决这些问题,我们在本文中提出了WiG,这是一种完全基于商用现货(COTS) WiFi基础设施和设备的无设备手势识别系统。与现有的基于射频(RF)的系统相比,WiG具有系统简单、成本极低和实用性高的特点。我们在室内环境中实施了WiG,并对其在两种典型场景下的性能进行了实验评估。结果表明,WiG在有视距场景下的平均识别准确率为92%,在无视距场景下的平均识别准确率为88%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WiG: WiFi-Based Gesture Recognition System
Most recently, gesture recognition has increasingly attracted intense academic and industrial interest due to its various applications in daily life, such as home automation, mobile games. Present approaches for gesture recognition, mainly including vision-based, sensor-based and RF-based, all have certain limitations which hinder their practical use in some scenarios. For example, the vision-based approaches fail to work well in poor light conditions and the sensor-based ones require users to wear devices. To address these, we propose WiG in this paper, a device-free gesture recognition system based solely on Commercial Off-The-Shelf (COTS) WiFi infrastructures and devices. Compared with existing Radio Frequency (RF)-based systems, WiG stands out for its systematic simplicity, extremely low cost and high practicability. We implemented WiG in indoor environment and conducted experiments to evaluate its performance in two typical scenarios. The results demonstrate that WiG can achieve an average recognition accuracy of 92% in line-of-sight scenario and average accuracy of 88% in the none-line-of sight scenario.
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